Evaluation the performance of commercial faba bean (Vicia faba L.) varieties on some morpho-physiolo by M. Mezbanur Rahman

Int. J. Agr. & Agri. R.

International Journal of Agronomy and Agricultural Research (IJAAR) ISSN: 2223-7054 (Print) Vol. 2, No. 8, p. 29-43, 2012 http://www.innspub.net RESEARCH PAPER

OPEN ACCESS

Evaluation the performance of commercial faba bean (Vicia faba L.) varieties on some morpho-physiological and N-fixing Traits under Eastern Ethiopia Million Fikreselassie School of Plant Sciences, Haramaya University, P. O. Box 138, Dire Dawa, Ethiopia Received: 15 July 2012 Revised: 14 August 2012 Accepted: 15 August 2012

Key words: Vicia faba L., commercial varieties, morpho-physiological, N-fixing, traits. Abstract Eight commercial faba bean varieties were evaluated under field and green-house condition in 2011 and 2012 respectively at Haramaya University to evaluate their performance for yield, yield components and incidence and severity of major disease. The experiment was laid out in RCBD with three replications. The mean squares of the genotypes were highly significant for days to maturity, stand count, reactions to rust, plant height, biomass yield and thousand seed weight implying that a wide range of variability has been obtained for the traits studied. The GCV ranged from 0.04% to 2606%, while the PCV varied between 0.4% and 2682.59% for the same characters. The estimated broad sense heritability ranged from 10.58 % to 98.72%. Genetic gains that could be expected from selecting the top 5% of the genotypes varied from 1.90% to 235.07%. Number of effective and non effective nodules per plant estimates high heritability and genetic advance. The first six PC accounted for more than 74% of the total variation. The first principal component which accounted for about 21% of the variability was due to Incidence of rust, number of pods and seeds per plant and stand count. The eight released faba bean varieties were grouped into three clusters and their differences were mainly attributed to the variation thousand seed weight and stand count. Seed yield had significant genotypic associations with plant height and number of pods per plant. In general, from this study Gachena adapted and suitable for production to the other part of the country where Gebelcho, Obse, Tumsa, and Cs20DK were recommended for production. *Corresponding

Author: Million Fikreselassie ď&#x20AC;Ş million_fikresilassie@yahoo.com/millionf@haramaya.edu.et

Fikreselassie

Page 29

Int. J. Agr. & Agri. R. Introduction

The National Agricultural Research System (NARS)

Faba bean (Vicia faba L.) is one of the major pulse

has developed and registered different improved

crops occupying about 35 percent both in terms of

faba bean suitable for national and regionally which

area coverage and volume of annual production of

are found to give yields ranging from 2.5 - 6 tone/ha

all pulses produced in the country and grown in the

on research fields and 1.8 - 4 ton/ha on farmers

highlands (1800-3000 meter above sea level) of

fields. As a result a number of improved varieties

Ethiopia (Gemechu et al, 2003). Ethiopia is now

were developed and released to farmer. Therefore,

considered as one of the centers of secondary

the objective of this piece of paper is to present and

diversity for faba bean (Yohannes, 2000).

discuss on the performance of released faba bean varieties to in terms of yield, yield components and

The inception of well organized faba bean breeding

incidence and severity of major disease

in Ethiopia was dated three decades back with the strong hybridization program commenced in mid

Material and methods

1980'. The main objective was to improve the

Seven nationally released faba bean varieties

productivity of the crop through the development of

developed by Holetta Agricultural Research Center

varieties tolerant/resistant to different constraints

along with a regionally released variety, Gachena

and suitable for cultivation under different agro

,from Haramaya university were considered in this

ecologies of the country (Asfaw et al 1994). Its

study. Gachena (EH91001-13-2) was released by

improvement, breeding, is based on variability

Haramaya

available in the local collection of indigenous

requirements set by the National Variety Release

landraces and hybridization made with exotic

committee for production in Eastern highlands of

germplasm

the country, primarily in areas with average annual

introduced

mostly

from

ICARDA

(Gemechu et al, 2003).

University

after

fulfilling

the

rain fall of 700 to 1000 mm. It is typically characterized by average seed yield of 17 to 30 q/ha

This crop has manifold advantages in the economic

and 11 to 28q/ha on research and farmer fields,

lives of the farming community in the high lands of

respectively (Million and Habtamu, 2012).

the country. It is a source of food, fed, cash to farmers. Also play significant role in soil fertility

The materials were tested under both field and

practices. However, its share in the countries pulse

green

export is small (Newton et al., 2011, Amanuel et al.,

respectively.

house

condition

2011

and

2012

1993, Tanner et al., 1991). Although the absolute figure is still small compared to the potential,

Field experiment

Ethiopia's export of faba beans has shown an

The field experiment was conducted at Haramaya

increase since the year 2000. Major market

University Research field located at 9 024â&#x20AC;&#x2122;N and

destinations for Ethiopian faba beans are Sudan,

42003â&#x20AC;&#x2122;E, in Ethiopia during 2011 main cropping

South Africa, Djibouti, Yemen, Russia and USA.

season. Haramaya has an altitude of 1980 meter above sea level. It was in semi-arid sub-tropical belt

It is evident from the report of entral statistical

of eastern Ethiopia. The area receives an average

authority (CSA, 2011), faba beans were planted to

annual rainfall of 870 mm. The soil is characterized

3.88 % (about 459,183.51 hectares), of the grain

as a fluvisol with a pH of 7.4 (Solomon, 2006).

crop area. The production obtained from faba beans, 3.43 % (about 6,977,983.87 quintals) of the

Treatments were arranged in RCBD with three

grain production

replications. Seeding was done in a plot of 5m X 4m with regular spacing of 10 cm between plants and 40 cm between rows. The layout and randomization were

Int. J. Agr. & Agri. R. as per the standard procedure set by Cochran and Cox

Results and discussion

(1957).

Analysis of variance The analysis of variance from the field experiment

the following data were collected during 2011 from

(Table 1) showed that the mean squares due to

the whole plot or from ten sample plants randomly

replication were highly significant for stand count

from each plot. Mean values of these samples were

and biomass yield, significant for number of pods

utilized to estimate the performance of each

per plant, seed yield per plot and per hectare

treatment for the traits under consideration. the

indicated differences between the three replications

following data such as; days to 50%flowering, days

(environment) and these are significant enough to

to 90% physiological maturity, grain filling period,

see the genetic performance of the commercial

stand count, chocolate spot, rust incidence, lodging,

varieties. It is evident from the results, mean

plant height, number of pods per plant, number of

squares due to genotypes were highly significant for

seeds per plant, number of seeds per pod, biomass

days to maturity, stand count, reactions to the

yield per plot, thousand seed weight, seed yield per

disease rust, plant height, biomass yield and

lot and per hectare.

thousand seed weight, and significant for number of seeds and pods per plant indicating the existence of

Green house experiment

sufficient variability among the released varieties

The same treatment was conducted under the green

regarding with these traits.

house condition in 2012. Two seeds per hole were placed carefully to ensure the first germination.

From the green house experiment (Table 2), the

Thinning was made after germination. Treatments

analysis of variance showed that the mean squares

were arranged in RCBD with three replications. Five

due to replication were not significant in all the

plants per pot were maintained and the following

traits under consideration, indicated homogenous

data were collected based on single plant bases.

environment. Mean squares due to genotypes

germination day, dry matter content, days to 50%

showed highly significant for germination day and

flowering, leaf number, plant height at 50% of

dry matter significant for number and dry weight of

flowering, number of tiller, number of effective

non effective nodules per plant. Here under green

nodule, number of non effective nodules, dry weight

house condition High efficiency of completely

of effective nodules, dry weight of non effective

randomized design over randomized completely

nodules

block design was noticed for all traits.

The data were subjected to the analyses of variance

The evaluated released faba bean varieties in this

(ANOVA) for randomized complete block design

study showed significant phenotypic variability in

was performed using the SAS program software

terms of plant morphology, phenology and yield

(SAS, 1996). The coefficients of variations at

attributes. These results are similar with the

phenotypic and genotypic levels were estimated

findings of other scholars like Gemechu et al., 2005.

using the formula adopted by Johnson et al. (1955). Broad-sense heritability (h2) for traits were estimated

Range of parameters

using the formula adopted by Allard (1960). Squared

It depicted from Table 3, the variety Tumsa showed

distance (D2) for each pair of cluster combinations

shorter days to maturity (137 days) indicated that it

was computed using the formula adopted by Singh

may be suitable to lower rainfall regions whereas

and

the late types, obse and Cs20DK with 145 and 146

genotypic correlation coefficients were estimated

days respectively, can be adapted to the highland

using the standard procedure suggested by Miller et

areas with dependable rainfall. This variability

al. (1958).

showed suitable varieties for the various agro-

Chaudhary

(1999)

and

Phenotypic

Int. J. Agr. & Agri. R. ecological zones of the country. The existence of

varieties. Whereas, Degaga yielded the smallest

variability in seed size is associated with seedling

seed size (508.80g) but exhibited high number of

vigour, emergence of seed and stress tolerance

seeds per plant. Generally, the broad spectrum of

(McCormic, 2004). Larger seeds have greater

variability observed among the released varieties for

cotyledon reserves and therefore can provide energy

different

to young seedlings at faster rate (Qui et al., 1994).

adaptation to different agro-ecological condition. It

Among the tested varieties Gebelcho and Moti had

was generally noted that all varieties had exhibited

high thousand seed size as a result they have a

some degree of nodulation, with a mean score of

potential to escape/ survive in drought environment

43.79 effective and 26.75 non effective nodules per

since they had large storage food in their

plant.

characters

indicates

possibilities

endosperm as compared with the rest tested Table 1. Analysis of variance for 15 traits of faba bean varieties tested under field condition in 2011. Variables DF DM GFP STD CHSP RUST LODG PH PPPL SPP SPPL BMY TSW SYLDP SYPH

MSR(2) Î˛ 1.50ns 6.00 ns 9.50 ns 477.04** 0.67 ns 0.04 ns 0.01 ns 18.37 ns 8.40* 0.01 ns 54.00 ns 16.00** 54.00 ns 9.28* 2312604*

MSG(7) 12.54 ns 31.6** 28.36 ns 334.94** 1.31 ns 3.59** 0.18 ns 99.88** 4.95* 0.06 ns 47.12* 12.26** 57856.82** 1.82ns 454389 ns

MSE 3.37 3.53 4.93 4.51 0.82 0.78 0.31 3.57 1.34 0.24 4.13 1.40 64.86 1.34 670.63

CV (%) 5.56 2.51 6.07 6.05 22.78 21.85 27.43 2.73 17.30 8.78 19.30 8.32 9.46 22.62 22.62

for

Int. J. Agr. & Agri. R.

Table 2. Analysis of variance for 10 traits of faba bean varieties tested under greenhouse condition in 2012. Variables

MSR(2) Î˛

MSG(7)

MSE

CV (%)

Gerday

0.98ns

15.61**

0.68

2.85

Drymt

1.88 ns

20.95**

1.87

11.61

4.04 ns

32.00 ns

3.54

7.27

LFN

5.79 ns

15.07 ns

4.20

9.61

PhF

16.25 ns

42.71 ns

5.95

10.15

NTILL

0.29 ns

5.31 ns

1.69

22.31

1856.23 ns

31.90

66.87

NNENOD

12.54 ns

429.52*

10.39

72.49

DwtENW

0.14 ns

0.11 ns

0.27

86.66

DwtNEN

0.05 ns

0.08*

0.14

65.61

NENOD

618.

79ns

*, ** Significant at 0.05 and 0.01 probability level respectively and ns non significant MSR= Mean Square due to replication, MSG= Mean Square due to genotypes, MSE= Mean Square due to error, CV%= Coefficient of variation in percentage. Î˛

Figures in parenthesis indicate degrees of freedom.

Gerday= germination day, Drymt= Dry matter, DF= Days to 50% flowering, LFN=Leaf number, PhF= Plant height at 50% of flowering, NTILL= Number of tiller, NENOD=Number of effective nodule, NNENOD= Number of non effective nodules, DwtENW= Dry weight of effective nodules, DwtNEN= Dry weight of non effective nodules.

Estimation of genotypic and phenotypic variations

the field, under the green house condition, high

High genotypic coefficient of variation was observed

heritability was estimated for all of the traits under

for thousand seed weight (2606.90%), followed by

consideration except leaf number per plant (Table

number

effective

non

3). These characters, therefore, may respond

Stand

effectively to phenotypic selection. However, low

count(140.67%),number of seed per plant (46.70%)

values of heritability were estimated for number of

(Table 3). However, low for numbe of seeds per pod

seeds

(0.04%) and temporal data, such as number of days

possibility of improvement for this character

to flower (0.648%). The estimated values of

through

phenotypic variances were in the range of 0.01 for

heritability estimates for seed weight (Shukla and

number of seeds per plant to 18402.20 for thousand

Sharma, 1978) were reported. This finding is thus in

seed weight. This finding is in contrast with

agreement with the results obtained in the present

Fikreselassie et al (2012) who reported high

investigation.

effective(369.05%)

(400.83%)

nodules

per

and

plant,

per

pod

(10.58%),

selection.

indicating

earlier

studies,

limited high

phenotypic variance in fenugreek for number of seeds per plant in fenugreek. The lowest and highest

Generally, heritability determines the effectiveness

genotypic variances were found for the same traits

of selection. The effectiveness of selection for a trait

respectively.

depends on the relative importance of the genetic and environmental factors in the expression of

Estimation of heritability in broad sense

phenotypic differences among genotypes in a

Estimates of heritability in broad sense under the

population (Singh,1990). The components of yield

field and green house condition are presented

that were most heritable in this faba bean

hereunder. Under the field, it were high for plant

population were plant height, thousand seed weight

height (97.64%), thousand seed weight (97.18%),

and dry matter.

resistance to rust (93.42%), number of days to

selection for these traits could lead to an increase in

maturity (88.74%) and flower (76.05%). In line with

seed yield.

Therefore, the simultaneous

Int. J. Agr. & Agri. R. Table 3. Estimates of minimum, mean and maximum value, variance and coefficient of variation at phenotypic (σ2p), genotypic (σ2g) level, heritability in broad sense (h2%), genetic advance in absolute (GA) and percent of mean (GAM) for 25 traits of Faba bean. Variables

Min

Mean

Max

σ 2p

56.67

59.75

62.67

0.50

137.33 78.00

141.00 81.25

146.00 86.67

7.19

σ 2g

GCV%

0.38

0.64

6.38

4.53

1.33

1.64

104.86

140.67

0.21

5.98

0.99

27.74

0.03

2.65

29.04

22.21

1.05

13.61

0.00

0.04

10.01

46.70

3.43

20.31

17883.2

2606.9

PCV%

h2%

GAM

0.84

76.05

5.29

8.85

5.10

88.74

6.46

4.58

2.68

61.00

6.20

7.63

217.25

64.75

6.02

8.08

7.93

75.38

1.28

35.58

29.69

93.42

1.50

41.95

3.53

74.85

0.48

42.55

22.75

97.64

7.19

5.50

24.28

56.04

1.55

20.03

0.40

10.58

0.05

1.90

68.23

68.44

5.83

27.22

30.70

66.15

1.91

11.32

2682.6

97.18

130.03

18.96

Under Field

GFP

2.18

STD

57.00

74.54

86.33

161.94

CHSP

3.00

3.58

4.33

0.28

RUST

2.33

3.58

5.00

1.06

LODG

1.00

1.13

1.67

0.04

119.00

130.75

137.00

29.74

PPPL

6.00

7.73

10.13

1.88

SPP

2.49

2.76

2.98

0.01

SPPL

16.87

21.43

27.60

14.62

BMY

13.87

16.88

19.67

5.18

852.03

18402.2

TSW

508.80 685.99

SYLDP SYLDH Under Green house Geday Drymt DFg LFN PhF NTILL NENOD NNENOD DwtENW DwtNEN

19.33

23.77

25.33

5.12

5.05

21.24

21.51

98.72

1.38

5.83

13.50

16.07

20.00

6.02

5.82

36.23

37.47

96.68

3.73

23.21

41.33

48.67

50.67

7.55

6.49

13.34

15.52

85.97

6.28

12.90

41.00

43.69

47.60

2.33

0.85

1.95

5.33

36.50

3.16

7.24

50.40

58.64

63.87

4.83

2.44

4.16

8.24

50.40

6.19

10.55

6.00

7.58

10.33

1.14

0.82

10.75

14.99

71.73

2.50

32.98

1.67

43.79

80.67

325.79

175.53

400.83

743.96

53.88

35.46

80.97

8.67

26.75

47.67

104.37

98.72

369.05

390.16

94.59

20.27

75.79

0.03

0.21

0.35

0.022

0.020

1.13

1.26

89.85

0.50

235.07

0.04 0.24 0.62 0.02 0.02 9.23 9.96 92.69 0.27 110.39 DF= Days to 50% flowering, DM= Days to 90% maturity, GFP= grain filling period, CHSP= chocolate spot, RUST= rust, LODG= logging, PH= plant height, PPPL= number of pods per plant, SPP= number of seeds per pod, SPPL= number of seeds per plant, BMY= biomass per plot, TSW= thousand seeds weight,

SYLDP= seed

yield per plot, SYLDH= seed yield per hectare, Gerday= germination day, Drymt= Dry matter, DFg= Days to 50% flowering in green house, LFN=Leaf number, PhF= Plant height at 50% of flowering, NTILL= Number of tiller, NENOD=Number of effective nodule, NNENOD= Number of non effective nodules, DwtENW= Dry weight of effective nodules, DwtNEN= Dry weight of non effective nodules.

Int. J. Agr. & Agri. R. Table 4. The eigen values and vectors of the correlation matrix for 22 traits of released faba bean varieties. Parameter Eigen value

PRIN1

PRIN2

PRIN3

PRIN4

PRIN5

PRIN6

5.083

3.486

2.835

2.637

2.136

1.697

% variance

21.18

14.53

11.81

10.99

8.90

7.07

Cumulative

21.18

35.70

47.52

58.50

67.40

74.47

Character DF

0.108

0.197

0.032

-0.135

-0.242

0.178

-0.080

-0.176

0.031

0.431

-0.184

0.298

STD

0.278

-0.040

0.307

0.019

0.171

0.182

ChSp

-0.208

-0.069

0.025

0.419

-0.115

0.226

Rust

0.312

0.072

-0.100

0.071

0.204

-0.152

Lodg

0.180

0.001

-0.339

0.159

-0.286

0.256

0.176

0.061

0.032

0.079

0.126

-0.040

PPPl

0.288

0.156

-0.192

0.133

0.043

0.326

Spp

0.061

0.170

-0.067

-0.275

0.306

0.288

SPPl

0.285

0.212

-0.185

0.036

0.158

0.369

Biom

-0.097

0.276

0.344

0.184

0.081

-0.009

TSW

-0.180

0.308

-0.187

-0.007

0.203

-0.242

Syldp

-0.179

0.254

0.398

0.046

0.077

0.196

Syldh

-0.179

0.254

0.398

0.046

0.077

0.196

Gerday

0.255

-0.304

0.224

0.074

0.198

-0.040

Drymt

-0.330

0.128

-0.215

0.054

0.145

0.014

LFN

-0.159

0.143

-0.100

-0.355

0.063

0.271

NTILL

-0.050

-0.243

-0.054

-0.184

0.363

0.208

NENOD

-0.229

-0.230

-0.142

0.179

0.275

0.199

NNENOD

0.175

0.266

0.001

0.311

0.004

-0.135

DwtEN

-0.202

-0.235

-0.111

0.202

0.353

0.008

DwtNEN

0.222

0.200

-0.039

0.275

0.268

-0.249

PRIN1, PRIN2, PRIN3, PRIN4 and PRIN5 = Principal component 1, 2, 3, 4 and 5 respectively, DF= Days to 50% flowering, DM= Days to 90% maturity, GFP= grain filling period, CHSP= chocolate spot, RUST= rust, LODG= logging, PH= plant height, PPPL= number of pods per plant, SPP= number of seeds per pod, SPPL= number of seeds per plant, BMY= biomass per plot, TSW= thousand seeds weight, SYLDP= seed yield per plot, SYLDH= seed yield per hectare, Gerday= germination day, Drymt= Dry matter, LFN=Leaf number, NTILL= Number of tiller, NENOD=Number of effective nodule, NNENOD= Number of non effective nodules, DwtENW= Dry weight of effective nodules, DwtNEN= Dry weight of non effective nodules.

Int. J. Agr. & Agri. R. Table 5. Mean, range, SD and CV% of genetic divergence in phonological and morphological traits of the three clusters of faba bean. Cluster I Character

Min

Max

CV%

62.67

III

Min

Max

56.67

59.00

61.33

3.56

CV%

Min

Max

CV%

58.00 60.27

3.91

8.06

7.41

58.67

137.33 141.60 146.00 1.32

0.93

138.00 140.00 142.00 2.00

2.82

140.00

GFP

78.00 81.33

86.67

4.37

23.48

80.67

81.00

81.33

0.33

0.13

81.33

STD

57.00

74.33

83.33

3.67

4.93

72.00

79.17

86.33

2.86

3.61

66.33

ChSp

3.00

3.80

4.33

0.63

16.64

3.00

0.00

3.67

Rust

2.33

3.40

5.00

0.82

24.01

4.33

4.67

5.00

0.82

17.49

2.33

Lodg

1.00

0.00

1.00

1.34

1.67

0.41

30.61

1.33

9.74

119.00

5.87

10.03

131.00

PPPl

6.00

7.05

8.13

1.30

18.41

8.60

9.37

10.13

1.79

19.17

7.87

Spp

2.49

2.70

2.81

0.22

8.33

2.80

2.89

2.98

0.40

13.97

2.85

SPPl

16.87

19.13

23.47

4.92

25.72

25.73

26.67

27.60

1.63

6.12

22.40

BMY

16.73

18.13

19.67

0.94

5.16

13.87

14.44

15.00

2.86

19.80

15.53

TSW SYLDP

131.00 133.93 137.00 5.70

526.97 685.25 852.03 16.51 6.00

11.99

824.37

66.80

6.93

3096.7 3233.3 328.1 10.59 2333.3 2383.3 2433.3 1592.2 66.80

6.19

6.47

0.66

2.41

122.67 126.33

10.59

508.80 618.64 728.47 74.18 4.67

4.77

4.87

3.18

3000. SYLPH

Geday

21.00

24.12

25.20

0.52

2.17

24.93

25.13

25.33

0.28

3466.7

1.13

19.33

Drywt

13.70

15.95

18.80

2.15

13.50

14.42

15.33

1.34

9.27

20.00

LFN

41.00

42.91

45.93

3.45

8.05

43.60

43.70

43.80

6.79

16.53

47.60

NTILL

6.00

7.33

8.33

1.70

23.22

7.00

8.67

10.33

1.78

20.53

6.67

NEND

1.67

44.87

80.67 40.07 81.01

28.67

45.67

62.67

20.41

42.38

34.67

NNEND

8.67

27.67

47.67

11.14

72.02

29.33

30.50

31.67

8.29

73.11

14.67

DWtEN

0.03

0.20

0.35

0.33

98.69

0.14

0.22

0.29

0.11

36.49

0.27

DwtNEN

0.04

0.26

0.62

0.15

69.31

0.25

0.27

0.30

0.18

75.11

0.10

Min, Mn and Max stands for minimum, mean and maximum value, SD= standard deviation, CV%= Coefficient of variance, DF= Days to 50% flowering, DM= Days to 90% maturity, GFP= grain filling period, CHSP= chocolate spot, RUST= rust, LODG= logging, PH= plant height, PPPL= number of pods per plant, SPP= number of seeds per pod, SPPL= number of seeds per plant, BMY= biomass per plot, TSW= thousand seeds weight, SYLDP= seed yield per plot, SYLDH= seed yield per hectare, Gerday= germination day, Drymt= Dry matter, LFN=Leaf number, NTILL= Number of tiller, NENOD=Number of effective nodule, NNENOD= Number of non effective nodules, DwtENW= Dry weight of effective nodules, DwtNEN= Dry weight of non effective nodules Table 6. Pair wise generalized squared distance (D2) among 3 clusters constructed from 8 released faba bean varieties. Cluster Cluster one

Cluster one 0.940

Cluster two Cluster three

Cluster two

Cluster three

8910**

4606**

2.772

9560** 0.00

**, significant at 1%

Int. J. Agr. & Agri. R.

Table 7. Estimates of correlation coefficients at phenotypic (above diagonal) and genotypic (below diagonal) levels of some 20 traits in Faba bean varieties. Traits DF

1.00

GFP

STD

CHSP

RUST

LODG

PPPL

SPP

0.181 -0.522**

-0.049

0.163

0.081

0.341

0.055

0.349

-0.183

0.397

1.00

0.744**

0.002

0.823**

-0.255

0.275

0.291

-0.032

-0.264

GFP

-0.246

0.792*

1.00

0.036

0.603**

-0.277

0.007

0.215

-0.265

-0.104

STD

-0.435

-0.251

0.024

1.00

-0.126

0.323

-0.130

-0.213

0.345

0.131

CHSP

0.405

0.755*

0.527

-0.566

1.00

-0.315

0.035

0.412*

RUST

-0.549

-0.473

-0.134

0.364

-0.625

1.00

0.239

-0.458*

0.505*

0.235

LODG

0.196

0.059

-0.068

-0.242

-0.315

0.044

1.00

-0.311

0.592**

-0.045

-0.431

-0.286

-0.341

-0.183

0.392

0.324

0.081

-0.535

0.577

PPPL

-0.118

-0.140

-0.069

0.101

-0.449

SPP

-0.666

-0.758*

-0.357

0.201

-0.758*

SPPL

-0.355

-0.373

-0.158

0.180

BMY

0.279

0.093

-0.088

-0.312

TSW

-0.331

-0.405

-0.207

-0.484

1.00

-0.318

0.737*

-0.619

1.00

0.111

0.581

0.218

-0.592

0.327

1.00

-0.615

0.650

0.646

-0.702*

0.954*

0.582

0.420

-0.088

-0.486

0.868**

-0.484

-0.537

0.081

-0.299

0.248

-0.139

0.199

0.510

-0.150

0.265

SYLDP

-0.053

0.014

0.050

-0.259

0.376

-0.537

-0.375

0.734*

0.654*

-0.270

SYLDH

-0.053

0.014

0.050

-0.259

0.376

-0.537

-0.375

0.734*

0.654*

-0.270

Drywt

-0.068

0.195

-0.765*

0.624

-0.428

-0.088

0.384

-0.311

-0.028

NENOD

0.304

0.450

-0.556

0.626

-0.297

-0.189

0.124

-0.346

-0.191

NNENOD

-0.180

-0.083

0.123

-0.125

0.344

0.112

0.231

0.384

-0.163

DwtEN

-0.026

0.694*

-0.330

0.724*

-0.249

-0.272

0.127

-0.330

-0.289

DwtNEN

-0.405

-0.280

0.298

-0.308

0.687

-0.016

-0.066

0.491

0.099

*, ** Significant at 0.05 and 0.01 probability level respectively DF= Days to 50% flowering, DM= Days to 90% maturity, GFP= grain filling period, CHSP= chocolate spot, RUST= rust, LODG= logging, PH= plant height, PPPL= number of pods per plant, SPP= number of seeds per pod, SPPL= number of seeds per plant, BMY= biomass per plot, TSW= thousand seeds weight, SYLDP= seed yield per plot, SYLDH= seed yield per hectare, Gerday= germination day, Drymt= Dry matter, LFN=Leaf number, NTILL= Number of tiller, NENOD=Number of effective nodule, NNENOD= Number of non effective nodules, DwtENW= Dry weight of effective nodules, DwtNEN= Dry weight of non effective nodules

Int. J. Agr. & Agri. R. Table 7 continue Traits DF DM GFP STD CHSP RUST LODG PH PPPL SPP SPPL BMY TSW SYLDP SYLDH Drywt NENOD NNENOD DwtEN DwtNEN

SPPL

BMY

TSW

SYLDP

SYLDH

Drywt

NENOD

NNENOD

DwtEN

DwtNEN

0.222

0.195

-0.157

-0.152

-0.031

-0.037

0.099

-0.176

-0.010

-0.136

0.020

-0.325

0.030

0.058

0.328

0.114

0.0303

-0.127

-0.175

0.129

-0.269

-0.116

0.377

0.020

-0.298

0.126

-0.592**

0.283

0.193

-0.179

0.285

-0.248

0.209

0.102

0.197

0.271

0.492*

0.071

0.324

-0.158

0.036

-0.302

-0.317

-0.266

0.319

-0.279

0.509*

-0.410*

-0.123

-0.095

0.192

-0.207

0.082

0.408*

0.263

0.135

0.206

0.142

-0.024

-0.187

-0.259

-0.151

0.338

-0.228

0.412*

0.099

0.091

-0.057

0.053

-0.182

0.035

-0.117

-0.205

-0.176

0.350

-0.276

0.418*

0.561**

-0.045

0.496*

-0.392

-0.369

0.646**

0.941**

-0.049

0.435*

-0.059

1.00

-0.039

-0.536 0.005

-0.312 0.288 -0.091 0.120 -0.014

1.00

0.200

0.710**

0.108

-0.035

0.284

-0.109

0.196

0.351

1.00

0.129

0.555**

0.057

0.163

0.103

0.223

1.00

1**

0.234

-0.040

0.015

-0.065

-0.092

1.00**

1.00

0.234

-0.040

0.015

-0.065

-0.092

0.509

1.00

0.433*

-0.197

0.461*

-0.201

-0.163

-0.162

0.541

1.00

-0.300

0.737**

-0.196

0.220

-0.211

-0.726*

1.00

-0.229

0.757**

-0.028

0.547

0.827*

-0.469

1.00

0.031

-0.073

-0.325

-0.646

0.894**

-0.420

1.00

-0.614

0.573

0.456

-0.614

0.573

0.456

-0.279

0.142

0.706*

-0.396

-0.049

0.110

0.342

0.462

0.178

-0.385

-0.056

0.047

0.524

0.311

0.235

Estimation of expected genetic advance

and 5.83% to 235.07% the same magnitude

Genetic gains that expected from selecting the top

respectively can be made by selection based on

5% of the genotypes, as a percent of the mean,

these traits under similar conditions to this study.

varied from 1.90% for number of seeds per pod to

The low values of expected genetic advance for the

42.55% for the trait lodging percentage in the field

traits like number of seed per pod and number of

and 5.83% for germination date to 235.07% for dry

days to flowering are due to low variability for the

weight of effective nodules per plant in the green

traits indicated by the low genotypic and phenotypic

house, indicating an increase of 1.90% to 42.55%

coefficient of variation values (Table 3). This

Int. J. Agr. & Agri. R. indicates the importance of genetic variability in

effective nodules per plant and days to maturity had

improvement through selection. Plant height,

negative

thousand seed weight, rust resistance and number

component accounted for 11.81% of the total

of days for maturity under the field condition and

variation and the seed yield per plant and per

number of effective and non effective nodules per

hectare and most of the yield contributing traits was

plant under the green house condition estimates

exhibiting positive effects. The traits days to

high heritability and genetic advance as compared

maturity and resistance to chocolate spot exerted

to other yield contributing traits. This suggests that

maximum and positive effect on the fourth

they may serve as important traits in indirect

component. Whereas, the traits number of tiller per

selection for higher seed yield. As observed in the

plant, dry weight of effective nodules and number of

present investigation, the low expected genetic

seeds per plant exerted high positive influence on

advance for number of seeds per pod was due to low

the fifth principal component. It is revealed from

variability for the traits.

the result number of seeds and pods per plant exert

impact

it.

The

third

principal

their maximum positive components on the sixth Principal component analysis

component. The traits that contributed most for the

In order to assess the pattern of variations,

first principal component were phenotypically

principal

negatively associated with the major traits of the

component

considering

the

analysis twenty

was two

done

variables

second

principal

component (Table 7). This

simultaneously. Six of the twenty-two principal

indicates there is variability among the traits of the

components accounted for more than 74% of the

improved faba bean varieties considered in this

total variation in the released faba bean varieties

investigation.

(Table 4). The first principal component accounted for 21.18% of the total variation. While eleven of the

Clustering of varieties and divergence analysis

twenty-two traits considered exerted positive effects

Genetic diversity plays an important role in plant

on this component and the rest of the traits exerted

breeding because hybrids between lines of diverse

negative effects of different magnitudes. Among

origin generally display a greater heterosis than

those traits having positive and greater influence

those between closely related strains. The average

include: Incidence of rust, number of pods and

linkage technique of clustering produced a more

seeds per plant, stand count, germination day, dry

understandable portrayal of the eight faba bean

weight of non effective nodules per in same order.

varieties by grouping them into three clusters, whereby different members within a cluster being

Conversely, dry matter, number of effective per

assumed to be more closely related in terms of the

plant, reaction to chocolate spot, dry weight of

trait under consideration with each other than those

effective nodules per plant, thousand seed weight,

members in different clusters. Similarly, members

seed yield per plant and per hectare, leaf number

in clusters with non-significant distance were

per plant and days to mature exerted negative

assumed to have more close relationship with each

influence. The second component accounting for an

other than they are with those in significantly

additional 14.53% of the total variation primarily

distant clusters. Table 5 indicates the range

illustrates the patterns of variations in thousand

(minimum

seed weight, biomass yield per plot, seed yield per

deviation and CV% of genetic divergence in

plant and per hectare which were found to have

phonological and morphological traits of the three

positive impacts on the second component but had

clusters and detail account of the characteristics of

negative

each cluster is presented hereunder.

impact

the

first

component.

Germination day, number of tiller per plant, dry weight of effective nodules per plant, number of

and

maximum),

mean,

standard

Int. J. Agr. & Agri. R. Cluster I: consisted of five varieties (Gebelcho,

In general, the differences between the clusters

Obse, Tumsa, Cs20DK and Gachena). Members in

were mainly attributed to the variation in thousand

this cluster laid on requiring long period for

seed weight and stand count. Other traits such as

flowering and maturity (late), high biomass yield,

days to flowering, reaction to chocolate, plant height

tall in height and high infestation by chocolate spot.

have

Intermediate

constellations. These traits were also the major

value

with

stand

count,

rust

infestation, thousand seed weight and seed yield.

contributed

equally

well

for

cluster

contributors to the principal one and two (Table 4).

Here, all the data undergoing in green house exhibited in the intermediate manner. However,

The maximum distance was found between cluster

low for yield contributing traits like number of pods

two and three (D2=9560) (Table 6). Cluster two

per plant, seed per pod and per plant and exhibited

constitutes two varieties Degagga and Dosha, while

resistance for lodging. So the varieties under this

cluster three constitutes a single variety Moti. The

cluster are suitable for highlands with relative high

second divergent clusters was cluster one and two

rain fall areas.

(D2= 8910). Cluster one constitutes five released varieties (Gebelcho, Obse, Tumsa, Cs20DK and

Cluster II: consisted of two varieties (Degagga

Gachena). Gachena was released from Haramaya

and Dosha), which were characterized by low in

University for Eastern part of the country. From

seed yield, biomass yield, thousand seed weight, dry

this study Gachena also deserves and adapt well to

matter, number of leaves per plant, and dry weight

the other part of the country where Gebelcho, Obse,

of effective nodules per plant. It also exhibited

Tumsa, and Cs20DK were recommended for

shorter in height and low infestation by chocolate

production.

spot (resistance). These materials in this cluster also exhibited high stand count, late in germination day,

Generally, maximum genetic segregation and

high number of tiller per plant, number of total

genetic recombination is expected from crosses that

(effective and non effective) nodules per plant, dry

involve parents from the clusters characterized by

weight

plant,

significant distances (Gemechu et al., 1997). In the

susceptible to rust, lodging and other yield

present investigation, therefore, crossing of the

components like number of pods per plant, seed per

varieties Degagga and Dosha with Moti will give

pod and per plant. Therefore Degagga and Dosha

rise to maximum genetic segregation. Among the

are

for

three clusters formed, cluster two showed the

developing the variety which resists the disease

maximum intra-cluster D2 value of 2.772. Since

chocolate spot.

cluster three contains sole variety, the intra-cluster

non

becoming

effective

suitable

nodules

for

gene

per

source

D2 value is zero (Table 6). The result revealed that Cluster III: Consisted of one variety (Moti) and it

even though cluster one contains the largest

was found to be the most superior variety interms of

number of varieties (five varieties), it had the

seed size, seed yield, dry matter content, number of

shortest intra-cluster distance. This indicates that

leaves per plant and dry weight of non effective

the varieties grouped in this cluster are more

nodules per plant. It also exhibited resistance in

similar as compared with the varieties in the second

rust infestation and earlier in days to flowering and

clusters. In a similar fashion, there were only two

germination day. However, low in stand count,

accessions for cluster two, but it was more divergent

number of tiller per plant, number of total nodules

as compared with the varieties present in the rest of

per plant and dry weight of non effective nodules

the clusters.

per plant. It yielded intermediate in the rest of the traits under studied. Moti can be used as a source for gene resistance the disease rust.

Int. J. Agr. & Agri. R. Analysis of correlation coefficient

In this particular investigation, in most of cases

The existence of strong positive correlation between

phenotypic and genotypic correlations closely

seed yield and different traits helps in identifying

agreed. The close agreement of phenotypic and

traits that could be used for indirect selection of

genotypic correlations may be due to the reduced

higher yielding cultivars (Steel and Torrie, 1984).

environmental variance (Hailu, 1988). Thus, the

Yield is a complex trait, which is controlled by many

phenotypic correlation coefficient reflects more or

genes (polygenic) and usually has low heritability

less the real association among the character

(Akinwale et al., 2011). Hence, simple traits that

considered.

have high genetic correlation with seed yield and high heritability could be used for indirect selection

The positive associations between characters imply

for seed yield. Table 7 summarizes genotypic and

the possibility of correlated response to selection

phenotypic correlation coefficients between all

and it follows that with the increase in one, will

possible pairs of the twenty traits recorded from the

entail an increase in another and the negative

eight released faba bean varieties.

correlation preclude the simultaneous improvement of those traits along with each other.

Seed yield had positive and significant genotypic correlations with plant height (r=0.734), number of

Acknowledgments

pods per plant (r=0.654). It also had positive and

The author wish to thank Mr. Mekonen Dagne for

highly significant phenotypic correlations with

the invaluable assistance in handling the field trial

biomass yield and significantly with plant height.

and laboratory work. The financial assistance from

However, seed yield negative and significant

Haramaya University, Vice-president for Research,

phenotypic correlations with rust incidence. The

for the research work is highly acknowledged.

positive significant correlation observed between seed yield and plant height indicates that tall plants

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